One of the hallmarks of neoplastic transformation is the alteration of the chemical and molecular composition of the cell surface. Progressive changes in surface molecule expression allow tumor cells to respond efficiently to external signals for growth and survival, to interact with host tissues, to achieve metastasis, and to avoid immune surveillance. The identification and targeting of tumor-specific surface markers may lead to improved diagnostics and therapeutics for cancer. The antigenic determinants of the tumor cell surface are highly complex, however, including proteins as well as carbohydrates and other posttranslational modification products, which cannot be, predicted from the expression levels of mRNA. The goal of this proposal is to develop antibody library-based methods, which promote efficient identification of tumor specific cell surface antigens, methods that are applicable to the identification of cell type-specific surface markers in general. A large, immunologically naive antibody phage display library has been constructed, which contains more than 100 million distinct human antibody fragments. This library has been selected, or "panned," on the surface of prostate cancer cells to identify prostate cancer specific antibodies. Moreover, the selection methodology has been adapted to isolate antibodies with specific functionality, for example, the ability to trigger receptor-mediated endocytosis. Significantly, these tumor-specific antibodies can be identified without prior knowledge of their target antigens. To further evaluate and develop this platform technology, we propose (1) to establish the molecular identify of antigens recognized by previously identified prostate cancer-specific antibodies, using mass spectrometry methods which are capable of analyzing posttranslational modifications. This study will increase our knowledge of tumor physiology and will facilitate the design of effective therapy; it will also help determine the exact contribution of post-translational modifications to the final makeup of the tumor epitope space. (2) To develop a high throughput subtractive selection strategy based on flow cytometric sorting to significantly improve selection efficiency and to obtain greater numbers of tumor specific phage antibodies. (3) Antibody identification efforts to date have focused on tumor cell lines in culture, which may not preserve all the clinically relevant antigens present on primary tumor cells. We therefore plan to develop methods, which allow selection of phage antibodies on tumor cells in situ, within their proper stromal contexts. We propose to combine phage antibody display with laser capture microdissection (LCM) to identify antibodies against individual tumor cells on frozen tissue slides. The resulting antibodies will have a very high likelihood of recognizing clinically relevant tumor antigens.